Skip to main content

Relief Visualization Toolbox Python library. It helps scientist visualize raster elevation model datasets.

Project description

PyPI Anaconda-Server Badge Anaconda-Server Badge

Relief Visualization Toolbox Python library

Relief Visualization Toolbox (RVT) was produced to help scientists visualize raster elevation model datasets. We have narrowed down the selection to include techniques that have proven to be effective for identification of small scale features. The default settings therefore assume working with high resolution digital elevation models derived from airborne laser scanning missions (lidar), however RVT methods can also be used for other purposes.

Sky-view factor, for example, can be efficiently used in numerous studies where digital elevation model visualizations and automatic feature extraction techniques are indispensable, e.g. in geography, archaeology, geomorphology, cartography, hydrology, glaciology, forestry and disaster management. It can even be used in engineering applications, such as predicting the availability of the GPS signal in urban areas.

Methods currently implemented are:

  • hillshading,
  • hillshading from multiple directions,
  • slope gradient,
  • simple local relief model,
  • multi-scale relief model,
  • sky illumination,
  • sky-view factor (as developed by our team),
  • anisotropic sky-view factor,
  • positive and negative openness,
  • local dominance,
  • multi-scale topographic position.

RVT for Python

The rvt Python package contains three modules:

  • rvt.vis for computing visualizations

  • rvt.blend for blending visualizations together

  • rvt.default for defining default parameters with methods to compute and save visualization functions using set parameters

References

When using the tools, please cite:

  • Kokalj, Ž., Somrak, M. 2019. Why Not a Single Image? Combining Visualizations to Facilitate Fieldwork and On-Screen Mapping. Remote Sensing 11(7): 747.
  • Zakšek, K., Oštir, K., Kokalj, Ž. 2011. Sky-View Factor as a Relief Visualization Technique. Remote Sensing 3: 398-415.

Installation

The RVT Python package can be installed using Conda or PyPI, and can be used in Python scripts, Jupyter Notebooks and ArcGIS Pro.

RVT can also be installed as a set of custom raster functions for ArcGIS, and a plugin for QGIS.

You can also clone the repository.

Conda

The rvt package is available from the Anaconda Cloud repository. Using Conda to install the rvt package will include all required libraries.

To use this method, first install Anaconda and Conda.

Then open Anaconda Prompt (Windows) or Terminal (MacOS) and run:

conda install -c rvtpy rvt_py

PyPI

Another option is to install the rvt-py package and required libraries using the Python Package Index (PyPI).

PyPI usually has problems installing gdal, so install gdal first to use this method.

Then open Command Prompt (Windows) or Terminal (MacOS) and run:

pip install rvt-py

Requirements

Required libraries (specified versions have been tested, other versions may also work):

  • numpy 1.19.2
  • scipy 1.5.2
  • gdal 3.0.2

We recommend using Python 3.6 or higher and a Conda environment (this works best with gdal).

Documentation

Documentation of the package and its use is available at Relief Visualization Toolbox in Python documentation.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please report any bugs and suggestions for improvements.

Acknowledgment

Development of RVT Python scripts was part financed by the Slovenian Research Agency core funding No. P2-0406, and by research project No. J6-9395.

License

This project is licensed under the terms of the Apache License.

About

RVT Python library by Žiga Kokalj, Žiga Maroh, Krištof Oštir, Klemen Zakšek and Nejc Čož, 2022.

It is developed in collaboration between ZRC SAZU and University of Ljubljana.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rvt_py-2.2.1.tar.gz (60.5 kB view details)

Uploaded Source

Built Distribution

rvt_py-2.2.1-py3-none-any.whl (66.6 kB view details)

Uploaded Python 3

File details

Details for the file rvt_py-2.2.1.tar.gz.

File metadata

  • Download URL: rvt_py-2.2.1.tar.gz
  • Upload date:
  • Size: 60.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for rvt_py-2.2.1.tar.gz
Algorithm Hash digest
SHA256 f91bc328ce1b849edb726f4e0ea275c0e72ba1bdbf4d3388bbf65af8615aa692
MD5 c33eb108d264b7889599a948e11cffa7
BLAKE2b-256 10e7b9668d03880a92750d52dc3ffc546462e332cb0a7cac33a1363341b453dd

See more details on using hashes here.

File details

Details for the file rvt_py-2.2.1-py3-none-any.whl.

File metadata

  • Download URL: rvt_py-2.2.1-py3-none-any.whl
  • Upload date:
  • Size: 66.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for rvt_py-2.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 f3b171e056d8a808b7c58d8ed74db6eb1b2088e728008e7a1c9f1e9fb1d2a513
MD5 7ebfb2ab6695e3fc8e556b1c62147826
BLAKE2b-256 40b472d0cccd4a473b179c12dc92b3116ed6654728dfe2d9a8d318b921888a2c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page